Add job to compute the context label from alignment #507
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Judyxujj
requested review from
albertz,
curufinwe,
christophmluscher,
JackTemaki,
Marvin84,
Atticus1806 and
kuacakuaca
mm/context_label.py
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| pastLabel = np.mod(popFutureLabel, n_contexts) | ||
| centerState = np.floor_divide(popFutureLabel, n_contexts) | ||
| centerState = np.floor_divide(centerState - hmm_state, 3) |
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This is not correct. Please see also the comment above.
Once the identity of right and left are popped, one is left with the center phoneme state information. Depending on how you dumped the state-tying options in RASR, you would do further steps to pop also word end class and hmm state info.
My suggestion here is that the class has a dictionary that has the label info, such as whether end of word or boundary classes are used, and what is the number of hmm state per phoneme. And then to apply the exact inverse function with respect to the implementation of RASR here
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or just parse the string representation of the allophone?
mm/context_label.py
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| pastLabel = np.mod(popFutureLabel, n_contexts) | ||
| centerState = np.floor_divide(popFutureLabel, n_contexts) | ||
| centerState = np.floor_divide(centerState - hmm_state, 3) |
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or just parse the string representation of the allophone?
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The code looks ok on the surface after a quick glance, but as I am not familiar with the logic I would prefer if others approve that have more knowledge of this. |
Co-authored-by: michelwi <michelwi@users.noreply.github.com>
Co-authored-by: michelwi <michelwi@users.noreply.github.com>
Co-authored-by: Albert Zeyer <zeyer@cs.rwth-aachen.de>
Co-authored-by: Albert Zeyer <zeyer@cs.rwth-aachen.de>
Co-authored-by: Albert Zeyer <zeyer@cs.rwth-aachen.de>
Co-authored-by: Albert Zeyer <zeyer@cs.rwth-aachen.de>
mm/context_label.py
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| :param alignment_cache_path: path to alginment cache | ||
| :param allophone_path: path to allohone | ||
| :param dense_tying_path: path to denser tying file |
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